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BioIngest

A self-service data platform for collecting, cleaning, and exploring biomedical datasets.

BioIngest automates the tedious work of downloading data from 30+ public databases, scraping competitor catalogs, running cleaning scripts, and publishing everything to a shared data lake. Product managers and researchers can browse, compare, and query data without writing code.

Browse S3 Bucket :material-folder-open:{ .md-button } Browse GitHub :material-github:{ .md-button } Open Athena :material-database-search:{ .md-button } Request a Source :material-plus-circle:{ .md-button .md-button--primary }


Data Explorer

Browse 28 biomedical data sources, 66 queryable tables, and 3 cross-reference mapping tables.

Click :material-table-eye: to preview real columns and rows before downloading.


Browse Data

Proteins & Targets
Dataset Description :material-table-eye: GitHub S3
uniprot/swissprot_tsv 570K reviewed proteins (15 cols) :material-table-eye: :material-github: :material-cloud:
uniprot/idmapping_human UniProt cross-references (5 cols) :material-table-eye: :material-github: :material-cloud:
string/protein_links Protein-protein interactions (3 cols) :material-table-eye: :material-github: :material-cloud:
interpro/protein2ipr Protein domain families (6 cols) :material-table-eye: :material-github: :material-cloud:
chembl/uniprot_mapping ChEMBL target IDs (4 cols) :material-table-eye: :material-github: :material-cloud:
complex_portal/homo_sapiens Protein complexes (19 cols) :material-table-eye: :material-github: :material-cloud:
markerdb/proteins 4K biomarker proteins (12 cols) :material-table-eye: :material-github: :material-cloud:
Disease & Pathway Associations
Dataset Description :material-table-eye: GitHub S3
diseases/knowledge Disease-gene associations (7 cols) :material-table-eye: :material-github: :material-cloud:
diseases/experiments Experiment-based associations :material-table-eye: :material-github: :material-cloud:
reactome/UniProt2Reactome 2.5M pathway memberships (6 cols) :material-table-eye: :material-github: :material-cloud:
ttd/targets Therapeutic targets & drugs :material-table-eye: :material-github: :material-cloud:
ttd/drugs Drug-target-indication triples :material-table-eye: :material-github: :material-cloud:
clinvar/variant_summary Variant-disease significance :material-table-eye: :material-github: :material-cloud:
gtex/median_tissue_tpm Tissue expression matrix :material-table-eye: :material-github: :material-cloud:
Ontologies
Dataset Description :material-table-eye: GitHub S3
mondo/mondo 47K disease terms + hierarchy :material-table-eye: :material-github: :material-cloud:
disease_ontology/doid 12K Disease Ontology terms :material-table-eye: :material-github: :material-cloud:
efo/efo 50K experimental factors :material-table-eye: :material-github: :material-cloud:
gene_ontology/go_basic 45K Gene Ontology terms :material-table-eye: :material-github: :material-cloud:
mesh/descriptors MeSH medical vocabulary :material-table-eye: :material-github: :material-cloud:
icd/icd10cm ICD-10-CM diagnosis codes :material-table-eye: :material-github: :material-cloud:
Competitors & Assay Platforms
Dataset Description :material-table-eye: GitHub S3
competitors_msd/msd_assays MSD assay specs (LOD, range) :material-table-eye: :material-github: :material-cloud:
competitors_msd/msd_products_full MSD full catalog (2640 products, 661 analytes) :material-table-eye: :material-github: :material-cloud:
competitors_quanterix/assays Quanterix Simoa specs (8 cols) :material-table-eye: :material-github: :material-cloud:
competitors_alamar/all_targets Alamar NULISAseq targets (26 cols) :material-table-eye: :material-github: :material-cloud:
competitors_nomic/omni_1000 Nomic Omni 1000 targets (990) :material-table-eye: :material-github: :material-cloud:
competitors_nomic/core_immune Nomic Core Immune (284) :material-table-eye: :material-github: :material-cloud:
competitors_nomic/core_cardiomet Nomic Core CardioMet (286) :material-table-eye: :material-github: :material-cloud:
competitors_nomic/flex Nomic Flex (1056) :material-table-eye: :material-github: :material-cloud:
somalogic/somascan_11k SomaScan 11K menu :material-table-eye: :material-github: :material-cloud:
Olink & HPA Proteomics
Dataset Description :material-table-eye: GitHub S3
olink/explore_ht Explore HT full panel (5,416 proteins) :material-github: :material-cloud:
olink/explore_3072 Explore 3072 (8 panels × ~368) :material-github: :material-cloud:
olink/reveal Reveal panel (1,034 proteins) :material-github: :material-cloud:
olink/flex Flex library (197 proteins) :material-github: :material-cloud:
olink/target_96 11 Target 96 panels (92 proteins each) :material-github: :material-cloud:
olink/focus Focus panel (33 proteins) :material-github: :material-cloud:
platform_overlap Reconciled overlap data (24 platforms) :material-github: :material-cloud:
hpa_olink/proteinatlas HPA full proteomics :material-table-eye: :material-github: :material-cloud:
Genomics & Variants
Dataset Description :material-table-eye: GitHub S3
gnomad/constraint Gene constraint (pLI, LOEUF) :material-table-eye: :material-github: :material-cloud:
ensembl/gene_info Gene annotations (GRCh38) :material-table-eye: :material-github: :material-cloud:
dbsnp/variant_freq Population variant frequencies :material-table-eye: :material-github: :material-cloud:
ukb_disease_assoc/pan_ukb UK Biobank GWAS :material-table-eye: :material-github: :material-cloud:

How it works

flowchart TB
    DB[(Public DBs\nUniProt, STRING, Reactome, ClinVar...)] --> DL
    COMP[Competitor Catalogs\nMSD, Quanterix, Nomic, RBM, Alamar, Roche...] --> DL
    INT[Internal Files\nOlink panels, assay lists, curated spreadsheets] --> DL

    DL[Download / Scrape] --> EDIT[Clean and Transform\nR scripts, merge tables, normalize columns]
    EDIT --> PUBLISH[Publish\nconvert to Parquet, upload to S3]

    PUBLISH --> GIT[GitHub / Git LFS\nversion-controlled files]
    PUBLISH --> S3[(S3 Data Lake\nParquet + Athena SQL)]

    GIT --> WIKI[Wiki / Data Explorer\nbrowse, preview, compare]
    S3 --> WIKI

What you can do

Task How
Browse available data Use the Data Explorer above -- preview columns and rows before downloading
Download raw files bioingest download-all or clone the repo (Git LFS)
Compare competitor panels Platform Overlap Matrix -- see which proteins each platform measures
Run cleaning scripts scripts/ folder -- R/Python scripts for merging and normalizing tables
Query with SQL Open Athena and query any table across all sources
Request a new source Request form -- tell us what you need and we'll add it

Mapping Tables

Cross-reference tables linking all sources through shared identifiers:

Table Rows Cols What it maps :material-table-eye: S3
protein_map 26,499 9 UniProt ↔ Ensembl ↔ STRING ↔ ChEMBL ↔ HGNC :material-table-eye: :material-cloud:
disease_map 31,884 10 MONDO ↔ EFO ↔ DOID ↔ MeSH ↔ ICD-10 :material-table-eye: :material-cloud:
drug_map 42,939 5 TTD drugs ↔ targets ↔ indications :material-table-eye: :material-cloud:

Don't see what you need?

Request a New Data Source :material-plus-circle:{ .md-button .md-button--primary }

We add new sources regularly. Tell us what database you'd like and we'll build the connector.